Data Engineer

Vivid Resourcing; Aarschot; Hybride; EUR 61 000 - 78 000; Plein temps

Avantages offerts par ce poste

Meal vouchers

Company car or mobility budget

Group insurance and hospitalisation

Résumé du poste

Vivid Resourcing is seeking a Data Engineer to design, develop and maintain scalable ETL/ELT pipelines using Python and SQL. You will build cloud-based data lakes and data warehouses, and develop data models for analytics, forecasting, BI, and AI/ML use cases.

The role emphasizes data quality, observability, and automated workflows with Airflow and dbt, plus experience with cloud stacks (Azure/AWS/GCP). Fluency in English is required, hybrid work in Belgium with focus near Aarschot/Leuven.

Qualifications

• 2–5 years of experience in data engineering or similar role.
• Strong Python and SQL
• Proven production ETL/ELT pipelines experience.
• Hands-on with Databricks, Snowflake, dbt, Airflow, Microsoft Fabric, or similar.
• Experience with Azure, AWS or GCP.
• Good knowledge of Apache Spark and modern data-platform architectures.
• Experience with Git, Docker, CI/CD, and cloud-native development.
• Kubernetes knowledge is a plus.
• Fluent in English.

Responsabilités

• Design, develop, and maintain scalable ETL/ELT data pipelines using Python and SQL.
• Build and optimise cloud-based data lakes, data warehouses, and modern data platforms.
• Develop reliable data models to support analytics, forecasting, BI, and AI/ML use cases.
• Implement data-quality checks, monitoring, testing, governance, and pipeline observability.
• Develop and maintain automated data workflows using orchestration tools like Airflow and dbt.
• Contribute to cloud-native development, CI/CD, automation, and infra improvements.

Connaissances

Python

SQL

2–5 years experience

English fluency

ETL/ELT pipelines

Git

Docker

CI/CD

Apache Spark

Databricks

Snowflake

dbt

Airflow

Microsoft Fabric

Azure

AWS

GCP

Kubernetes

Outils

Databricks

Snowflake

dbt

Airflow

Microsoft Fabric

Azure

AWS

GCP

Docker

Kubernetes

Apache Spark

Git

Description du poste

You'll be joining a technology company using data, software, and AI to drive efficiency, automation, and sustainability across manufacturing and industrial operations. The work will consist of IoT and industrial data, building scalable data platforms that support analytics, forecasting, and AI-driven solutions.

Responsibilities

• Design, develop, and maintain scalable ETL/ELT data pipelines using Python and SQL.
• Build and optimise cloud-based data lakes, data warehouses, and modern data platforms.
• Develop reliable data models supporting analytics, forecasting, business intelligence, and AI/ML use cases.
• Implement data-quality checks, monitoring, testing, governance, and pipeline observability.
• Develop and maintain automated data workflows using orchestration and transformation tools such as Airflow and dbt.
• Contribute to cloud-native development, CI/CD, automation, and infrastructure improvements.
• Work with technologies such as Azure, AWS, GCP, Snowflake, Microsoft Fabric, Docker, and Kubernetes.

Your Profile

• 2–5 years of experience as a Data Engineer or in a similar data-focused engineering role.
• Strong programming skills in Python and SQL.
• Proven experience building and maintaining production ETL/ELT pipelines.
• Hands-on experience with one or more modern data technologies such as Databricks, Snowflake, dbt, Airflow, Microsoft Fabric, or similar.
• Experience working with Azure, AWS, or GCP.
• Good understanding of Apache Spark and modern data-platform architectures.
• Experience with Git, Docker, CI/CD, and cloud-native development.
• Knowledge of Kubernetes is an advantage.
• Fluent in English.

What's on Offer

• Competitive salary of up to €6,000 gross/month, depending on experience.
• Company car or mobility budget.
• Hybrid working model with a base in Aarschot/Leuven.
• Meal vouchers.
• Group insurance and hospitalisation insurance.
• Ongoing technical training and certification opportunities.
• Clear career progression towards Senior Data Engineer, Data Architect, or Tech Lead.
• Opportunity to work with a modern technology stack including Databricks, Snowflake, Microsoft Fabric, Azure, AWS, GCP, dbt, Airflow, and Apache Spark.
• Opportunity to work with industrial, IoT, and time-series data.
• The chance to contribute to real-world projects focused on manufacturing efficiency, automation, sustainability, and data-driven decision-making.